204 search results - page 2 / 41 » Learning locally minimax optimal Bayesian networks |
ML
2006
ACM
13 years 5 months ago
2006
ACM
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
ICPR
2008
IEEE
14 years 6 months ago
2008
IEEE
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
UAI
1997
13 years 6 months ago
1997
Recently several researchers have investigated techniques for using data to learn Bayesian networks containing compact representations for the conditional probability distribution...
UAI
2000
13 years 6 months ago
2000
Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
NN
2002
Springer
13 years 4 months ago
2002
Springer
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...